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Competitor Landscape

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superamped
competitor-landscape

Use this skill to synthesize research on two or more competitors into feature and pricing comparisons, positioning, SWOT, moat analysis, and strategic recommendations. Trigger it after individual competitor profiles exist or when preparing a market landscape.

Overview

Publishersuperamped
Repositoryai-marketing-skills
Skill namecompetitor-landscape
Stars
73
Forks
6
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by superamped on GitHub. Read the source before you install it.

Installation

Install the Competitor Landscape AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/superamped/ai-marketing-skills/tree/main/skills/research/competitor-landscape
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/superamped/ai-marketing-skills.git /tmp/ai-marketing-skills
mkdir -p .claude/skills
cp -r /tmp/ai-marketing-skills/skills/research/competitor-landscape .claude/skills/competitor-landscape
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Competitor Landscape in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Competitor Landscape on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Competitor Landscape is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Competitor Landscape

Usage

Use after analyzing 2+ competitors — you have individual profiles and need the comparative view. Also useful for preparing a board deck, investor update, or strategy doc that needs a market landscape section.

Process

Step 1: Gather Inputs

Ask the user for:

  1. Your product info — name, key features, pricing, differentiators
  2. Competitor data — for at least 2 competitors, provide for each:
    • Name and URL
    • Key features
    • Pricing (model, tiers, price points)
    • Target audience
    • Positioning (their headline/value prop)
    • Strengths and weaknesses
    • Social proof signals (customer count, notable logos, review scores)
  3. Custom axes for positioning map (optional) — default: market presence vs. product breadth

If the user has previously run competitor-site-analysis or competitor-content-analysis, they can reference those outputs.

Step 2: Feature Comparison Matrix

Build a side-by-side feature comparison across all competitors and the user's product:

Feature / CapabilityYour ProductCompetitor ACompetitor BCompetitor C
[feature 1][status][status][status][status]
[feature 2][status][status][status][status]

Status values: Full / Partial / Missing / Unknown

Include:

  • Core features that define the category (everyone should have these)
  • Differentiating features (only some competitors have)
  • Your unique features (only you have — highlight these)
  • Features competitors have that you don't (gaps to assess)

Sort rows by strategic importance, not alphabetically.

Step 3: Pricing Comparison

Build a pricing comparison table:

DimensionYour ProductCompetitor ACompetitor BCompetitor C
Model
Free tier
Entry price
Mid-tier price
Enterprise
Value metric
Annual discount
Trial
Key upgrade trigger

Pricing signals to flag:

  • Where you're significantly cheaper or more expensive than the market
  • Competitors using per-seat pricing where value doesn't scale with headcount (vulnerability)
  • Competitors with no free tier in a PLG market (acquisition barrier)
  • Mismatches between pricing model and GTM motion

Step 4: Positioning Map

Plot all competitors + your product on a 2x2 positioning map.

Default axes: Market Presence (low → high) vs. Product Breadth (focused → broad)

Score each company 1-10 on both axes:

  • Market presence — traffic volume, review count, brand recognition signals, funding stage
  • Product breadth — number of features, integrations, use cases served

Alternative axis options (offer to the user):

  • Customer satisfaction (from review scores) vs. Market share (from traffic)
  • Price level (low → high) vs. Feature depth (basic → advanced)
  • PLG friendliness (self-serve → sales-required) vs. Enterprise readiness (SMB → enterprise)

Present as a labeled quadrant:

                    High Market Presence
                          |
         Established      |      Market Leaders
         Niche Players    |
    ----------------------+----------------------
                          |
         Emerging         |      Growing
         Focused          |      Contenders
                          |
                    Low Market Presence

    Focused ←————— Product Breadth ——————→ Broad

Place each competitor and your product in the appropriate quadrant. Identify the gap: Where is there open space on the map? That's potential positioning territory.

Step 5: Aggregate SWOT

Synthesize across all competitors into a landscape-level view:

Strengths across competitors — what does the market generally do well? These are table stakes you must match.

Common weaknesses — what do multiple competitors struggle with? These are opportunities.

Industry opportunities — macro trends, technology shifts, or market gaps that no competitor has captured yet.

Industry threats — forces that affect everyone in this space (regulation, new entrants, platform risk, commoditization).

Step 6: Moat Landscape

Summarize the moat picture across all competitors:

MoatCompetitor ACompetitor BCompetitor CYou
Network effects
Switching costs
Scale economies
Brand recognition
Regulatory / IP
Distribution
Data advantage

Key insights:

  • Moats that NO competitor has built = opportunity to build first-mover defensibility
  • Moats that ALL competitors have = table stakes, not differentiators
  • Your unique moats = lean into these in positioning

Step 7: Content Comparison (if data available)

If competitor data includes content strategy info, compare content approaches:

Content TypeCompetitor ACompetitor BCompetitor CYou
Blog
Comparison pages
Guides / pillars
Glossary / programmatic
Templates / tools
Gated content

If no content analysis data exists, skip this section and note it.

Step 8: Strategic Recommendations

Synthesize everything into actionable recommendations:

Where you win — your clearest competitive advantages based on feature gaps, pricing position, moat differences, and competitor weaknesses. Be specific.

Where you're vulnerable — honest assessment of where competitors are ahead. What would you need to invest in to close the gap?

Market gaps — opportunities no one is serving well, informed by:

  • Empty space on the positioning map
  • Features no competitor offers
  • Audience segments being ignored
  • Pricing models no one has tried

Positioning recommendation — based on the full landscape, where should you position? What's your angle? What should you NOT compete on?

Messaging landmines — claims competitors make that you should avoid competing on directly (because they're stronger there) or because they're becoming commoditized.

Output Format

# Competitive Landscape: [Product Name]

**Date:** [current date]
**Competitors:** [list]

## Feature Comparison
[matrix from Step 2]

## Pricing Comparison
[table from Step 3]

## Positioning Map
[quadrant from Step 4]

## Aggregate SWOT
[landscape-level SWOT from Step 5]

## Moat Landscape
[moat comparison from Step 6]

## Content Comparison
[content type coverage from Step 7, if available]

## Strategic Recommendations

### Where You Win
[from Step 8]

### Where You're Vulnerable
[from Step 8]

### Market Gaps
[from Step 8]

### Positioning Recommendation
[from Step 8]

### Messaging Landmines
[from Step 8]

Rules

  • Need at least 2 competitors for comparison. A landscape analysis with one competitor is just a profile.
  • Never invent data — if information is missing for a competitor, note "data not available."
  • Never present a positioning map without explaining why you chose the axes.
  • Never make strategic recommendations without citing evidence from the data.
  • If competitor data has inconsistent depth (one has full pricing, another doesn't), flag that comparison will be uneven.
  • If the market appears highly fragmented (5+ direct competitors with no clear leader), note this.
  • Be honest if the user's product appears to be in a weak position on the map — suggest what to improve.
  • The positioning map is most valuable when you customize the axes to match your strategic question.

Frequently asked questions

What does the Competitor Landscape AI skill do?

Use this skill to synthesize research on two or more competitors into feature and pricing comparisons, positioning, SWOT, moat analysis, and strategic recommendations. Trigger it after individual competitor profiles exist or when preparing a market landscape.

Why use Competitor Landscape on TypingMind?

Because you install it once and use it with any model. Competitor Landscape is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Competitor Landscape in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/superamped/ai-marketing-skills/tree/main/skills/research/competitor-landscape. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Competitor Landscape?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Competitor Landscape?

As many as you like. As long as a model supports skills, you can use Competitor Landscape with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Competitor Landscape AI skill free?

Yes. It is published on GitHub by superamped under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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